What

ImageLayer is an image decomposition tool that turns a flat JPG, PNG, or WebP file into multiple editable transparent PNG layers. It is aimed at designers, e-commerce sellers, and content creators who need reusable parts from a finished image when the original layered source file is unavailable. Its positioning appears to be broader than a background remover, focusing on multi-part layer separation for editing and reuse.

Features

Multi-layer image separation: Splits one flat image into several transparent layers such as background, objects, and foreground details, which helps with reuse and layout changes.
Selectable layer counts: Supports Auto, 2, 4, 6, or 8 layers, letting users balance cleaner separation against credit usage.
In-browser layer preview: Shows generated layers before export and allows visibility toggling, so users can inspect separation quality before downloading.
PNG and ZIP export: Downloads layers individually as transparent PNGs or bundles them in a ZIP for editing handoff and production workflows.
Credit-based usage model: Uses one-time credits with no subscription, and failed generations are refunded automatically.

Helpful Tips

Use clear images with visible edges and simple overlaps; the page indicates these conditions usually produce stronger layer separation.
Start with Auto when the number of meaningful parts is unclear, since the tool recommends it for cleaner results.
Treat outputs as editable assets rather than full replacements for original PSD or Figma files; the site’s FAQ framing suggests limits to AI layer separation.
Check the online preview carefully before downloading, especially for small text, shadows, or overlapping details that may be harder to separate cleanly.

OpenClaw Skills

A likely OpenClaw use case would be a creative-ops or e-commerce asset workflow that routes flat marketing images through ImageLayer, reviews generated parts, and organizes approved PNG layers for downstream editing, catalog updates, or campaign localization. Although the page does not mention native integrations, plausible OpenClaw skills could include asset intake, image triage, layer-quality review, naming and packaging workflows, and handoff agents for design teams. Combined with OpenClaw, this could reduce manual rebuild work for designers and marketplace teams that often inherit only flattened image files.